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[Versioning] Deprecations for 0.4 #2109

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merged 12 commits into from
Apr 25, 2024
Merged

[Versioning] Deprecations for 0.4 #2109

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vmoens Apr 24, 2024
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@vmoens
vmoens committed Apr 24, 2024
commit 49b015df5a5413a9344cf725048c8a4d42da6dde
6 changes: 3 additions & 3 deletions test/test_shared.py
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Original file line number Diff line number Diff line change
Expand Up @@ -64,7 +64,7 @@ def test_shared(self, indexing_method):
batch_size=[],
).share_memory_()
elif indexing_method == 1:
subtd = td.get_sub_tensordict(0)
subtd = td._get_sub_tensordict(0)
elif indexing_method == 2:
subtd = td[0]
else:
Expand Down Expand Up @@ -182,14 +182,14 @@ def test_memmap(idx, dtype, large_scale=False):
torchrl_logger.info("\nTesting writing to TD")
for i in range(2):
t0 = time.time()
sub_td_sm = td_sm.get_sub_tensordict(idx)
sub_td_sm = td_sm._get_sub_tensordict(idx)
sub_td_sm.update_(td_to_copy)
if i == 1:
torchrl_logger.info(f"sm td: {time.time() - t0:4.4f} sec")
torch.testing.assert_close(sub_td_sm.get("a"), td_to_copy.get("a"))

t0 = time.time()
sub_td_sm = td_memmap.get_sub_tensordict(idx)
sub_td_sm = td_memmap._get_sub_tensordict(idx)
sub_td_sm.update_(td_to_copy)
if i == 1:
torchrl_logger.info(f"memmap td: {time.time() - t0:4.4f} sec")
Expand Down
45 changes: 21 additions & 24 deletions test/test_transforms.py
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Expand Up @@ -785,7 +785,7 @@ def test_transform_env_clone(self):

@pytest.mark.parametrize("dim", [-1])
@pytest.mark.parametrize("N", [3, 4])
@pytest.mark.parametrize("padding", ["zeros", "constant", "same"])
@pytest.mark.parametrize("padding", ["constant", "same"])
def test_transform_model(self, dim, N, padding):
# test equivalence between transforms within an env and within a rb
key1 = "observation"
Expand Down Expand Up @@ -838,7 +838,7 @@ def test_transform_model(self, dim, N, padding):

@pytest.mark.parametrize("dim", [-1])
@pytest.mark.parametrize("N", [3, 4])
@pytest.mark.parametrize("padding", ["same", "zeros", "constant"])
@pytest.mark.parametrize("padding", ["same", "constant"])
@pytest.mark.parametrize("rbclass", [ReplayBuffer, TensorDictReplayBuffer])
def test_transform_rb(self, dim, N, padding, rbclass):
# test equivalence between transforms within an env and within a rb
Expand Down Expand Up @@ -870,7 +870,7 @@ def test_transform_rb(self, dim, N, padding, rbclass):

@pytest.mark.parametrize("dim", [-1])
@pytest.mark.parametrize("N", [3, 4])
@pytest.mark.parametrize("padding", ["same", "zeros", "constant"])
@pytest.mark.parametrize("padding", ["same", "constant"])
def test_transform_as_inverse(self, dim, N, padding):
# test equivalence between transforms within an env and within a rb
in_keys = ["observation", ("next", "observation")]
Expand Down Expand Up @@ -987,7 +987,7 @@ def test_transform_no_env(self, device, d, batch_size, dim, N):
assert v1 is not v2

@pytest.mark.skipif(not _has_gym, reason="gym required for this test")
@pytest.mark.parametrize("padding", ["zeros", "constant", "same"])
@pytest.mark.parametrize("padding", ["constant", "same"])
@pytest.mark.parametrize("envtype", ["gym", "conv"])
def test_tranform_offline_against_online(self, padding, envtype):
torch.manual_seed(0)
Expand Down Expand Up @@ -1027,10 +1027,7 @@ def test_tranform_offline_against_online(self, padding, envtype):
@pytest.mark.parametrize("device", get_default_devices())
@pytest.mark.parametrize("batch_size", [(), (1,), (1, 2)])
@pytest.mark.parametrize("d", range(2, 3))
@pytest.mark.parametrize(
"dim",
[-3],
)
@pytest.mark.parametrize("dim", [-3])
@pytest.mark.parametrize("N", [2, 4])
def test_transform_compose(self, device, d, batch_size, dim, N):
key1 = "first key"
Expand Down Expand Up @@ -4177,11 +4174,11 @@ def test_observationnorm(
)
observation_spec = on.transform_observation_spec(observation_spec)
if standard_normal:
assert (observation_spec.space.minimum == -loc / scale).all()
assert (observation_spec.space.maximum == (1 - loc) / scale).all()
assert (observation_spec.space.low == -loc / scale).all()
assert (observation_spec.space.high == (1 - loc) / scale).all()
else:
assert (observation_spec.space.minimum == loc).all()
assert (observation_spec.space.maximum == scale + loc).all()
assert (observation_spec.space.low == loc).all()
assert (observation_spec.space.high == scale + loc).all()

else:
observation_spec = CompositeSpec(
Expand Down Expand Up @@ -5097,9 +5094,9 @@ def test_keys_length_errors(self, in_keys, reset_keys, out_keys, batch=10):
f"Could not match the env reset_keys {reset_keys} with the in_keys {in_keys}"
),
):
t.reset(td)
t._reset(td, td.empty())
else:
t.reset(td)
t._reset(td, td.empty())


class TestReward2Go(TransformBase):
Expand Down Expand Up @@ -6149,8 +6146,8 @@ def test_transform_no_env(self, keys, batch, device):
observation_spec
)
assert observation_spec.shape == torch.Size([3, 16, 16])
assert (observation_spec.space.minimum == 0).all()
assert (observation_spec.space.maximum == 1).all()
assert (observation_spec.space.low == 0).all()
assert (observation_spec.space.high == 1).all()
else:
observation_spec = CompositeSpec(
{
Expand Down Expand Up @@ -6198,8 +6195,8 @@ def test_transform_compose(self, keys, batch, device):
observation_spec
)
assert observation_spec.shape == torch.Size([3, 16, 16])
assert (observation_spec.space.minimum == 0).all()
assert (observation_spec.space.maximum == 1).all()
assert (observation_spec.space.low == 0).all()
assert (observation_spec.space.high == 1).all()
else:
observation_spec = CompositeSpec(
{
Expand Down Expand Up @@ -8039,14 +8036,14 @@ def test_independent_reward_specs_from_shared_env(self):
t1_reward_spec = t1.reward_spec
t2_reward_spec = t2.reward_spec

assert t1_reward_spec.space.minimum == 0
assert t1_reward_spec.space.maximum == 4
assert t1_reward_spec.space.low == 0
assert t1_reward_spec.space.high == 4

assert t2_reward_spec.space.minimum == -2
assert t2_reward_spec.space.maximum == 2
assert t2_reward_spec.space.low == -2
assert t2_reward_spec.space.high == 2

assert base_env.reward_spec.space.minimum == -np.inf
assert base_env.reward_spec.space.maximum == np.inf
assert base_env.reward_spec.space.low == -np.inf
assert base_env.reward_spec.space.high == np.inf

def test_allow_done_after_reset(self):
base_env = ContinuousActionVecMockEnv(allow_done_after_reset=True)
Expand Down
4 changes: 2 additions & 2 deletions torchrl/envs/libs/dm_control.py
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Original file line number Diff line number Diff line change
Expand Up @@ -80,8 +80,8 @@ def _dmcontrol_to_torchrl_spec_transform(
shape = torch.Size([1])
return BoundedTensorSpec(
shape=shape,
low=spec.minimum,
high=spec.maximum,
low=spec.low,
high=spec.high,
dtype=dtype,
device=device,
)
Expand Down
4 changes: 2 additions & 2 deletions torchrl/envs/libs/jumanji.py
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Original file line number Diff line number Diff line change
Expand Up @@ -67,8 +67,8 @@ def _jumanji_to_torchrl_spec_transform(
dtype = numpy_to_torch_dtype_dict[spec.dtype]
return BoundedTensorSpec(
shape=shape,
low=np.asarray(spec.minimum),
high=np.asarray(spec.maximum),
low=np.asarray(spec.low),
high=np.asarray(spec.high),
dtype=dtype,
device=device,
)
Expand Down
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